---
id: deployment
title: Deploying migrations from Atlas Cloud
---

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import TabItem from '@theme/TabItem';

### Deploying without Atlas Cloud

A common way to deploy migrations using Atlas (or any other migration tool) is similar to this:

* When changes are merged to the `main` branch, a CI/CD pipeline is triggered.
* The pipeline builds an artifact (usually a Docker image) that includes the migration directory content
  and Atlas itself.
* The artifact is pushed to a registry.
* The deployment process is configured to use this newly created image to run the migrations
  against the production database.

This process is a common practice, but it requires setting up a CI/CD pipeline (including storage, permissions,
and other glue) for each service, adding another layer of complexity.

### Why deploy from Atlas Cloud?

Atlas Cloud streamlines deploying migrations by providing a single place to manage migrations for all your services. After connecting
your migration directory to Atlas Cloud, it is automatically synced to a central location on every commit to your main branch.
Once this setup (which takes less than one minute) is complete, you can deploy migrations from Atlas Cloud to any environment
with a single command (or using popular CD tools such as Kubernetes and Terraform).

## Deploying migrations from Atlas Cloud

Atlas supports the concept of [_Data Sources_](/atlas-schema/projects#data-sources), which enables users to retrieve
information stored in an external service or database. To deploy migrations directly from your cloud account, use the
[`remote_dir`](/atlas-schema/projects#data-source-remote_dir) data source. This feature allows users to configure Atlas to read
the content of the migration directory directly from their cloud account, thereby eliminating the need to build custom
artifacts or docker images with the directory content.

Here is an example of how to configure the `remote_dir` data source:

```hcl title="atlas.hcl" {1-15}
variable "cloud_token" {
  type = string
}

atlas {
  cloud {
    token = var.cloud_token
  }
}

data "remote_dir" "migrations" {
  // The name of the migration directory in Atlas Cloud.
  // In this example, the directory is named "myapp".
  name = "myapp"
}

env {
  // Set environment name dynamically based on --env value.
  name = atlas.env
  migration {
    dir = data.remote_dir.migrations.url
  }
}
```

After configuring the `remote_dir` data source, you can deploy migrations from Atlas Cloud using the following command:

```shell
atlas migrate apply \
  --url "<DATABASE_URL>" \
  --config file://path/to/atlas.hcl \
  --env prod \
  --var cloud_token="<ATLAS_TOKEN>"
```

## Visualizing Migration Runs

Schema migrations are an integral part of application deployments, yet the setup might vary between different applications and teams.
Some teams may prefer using init-containers, while others run migrations from a structured CD pipeline. There are also those who opt for Helm
upgrade hooks or use our Kubernetes operator. The differences also apply to databases. Some applications work with one database,
while others manage multiple databases, often seen in [multi-tenant applications](/blog/2022/10/27/multi-tenant-support).

However, across all these scenarios, there's a shared need for a single place to view and track the progress of executed
schema migrations. This includes triggering alerts and providing the means to troubleshoot and manage recovery if
problems arise.

When you use the configuration above with a valid token, Atlas will log migration
runs in your cloud account. Here's a demonstration of how it looks in action:

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<TabItem label="Single Deployment" value="single">

[![](https://atlasgo.io/uploads/cloud/images/public-tenant-deployment.png)](https://gh.atlasgo.cloud/deployments/51539607559)

</TabItem>
<TabItem label="Multi-Tenant Deployment" value="mt">

[![](https://atlasgo.io/uploads/cloud/images/multi-tenant-deployment.png)](https://gh.atlasgo.cloud/deployments/sets/94489280524)

</TabItem>
</Tabs>

